2017/05/30 by Stefano Dafarra, Francesco Romanò, Dafarra, Stefano +6
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Neuroscience · #FOS: Computer and information sciences #Genetic Neurodegenerative Diseases #Muscle Physiology and Disorders #Prosthetics and Rehabilitation Robotics #Real-time simulation and control systems #Robotic Locomotion and Control #Robotics (cs.RO) #cs.RO
paper · pdf · doi:10.48550/arxiv.1705.10635
openalex publication_date 2017/05/30 · arxiv created 2017/07/28 · arxiv updated 2017/07/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
When balancing, a humanoid robot can be easily subjected to unexpected disturbances like external pushes. In these circumstances, reactive movements as steps become a necessary requirement in order to avoid potentially harmful falling states. In this paper we conceive a Model Predictive Controller which determines a desired set of contact wrenches by predicting the future evolution of the robot, while taking into account constraints switching in case of steps. The control inputs computed by this strategy, namely the desired contact wrenches, are directly obtained on the robot through a modification of the momentum-based whole-body torque controller currently implemented on iCub. The proposed approach is validated through simulations in a stepping scenario, revealing high robustness and reliability when executing a recovery strategy.